openmp

问题 Assume I have a method that multiplies two std::vector : double multiply(std::vector<double> const& a, std::vector<double> const& b){ double tmp(0); /*here I could easily do a parallelization with*/ /*#pragma omp parallel loop for*/ for(unsigned int i=0;i<a.size();i++){ tmp += a[i]*b[i]; } return tmp; } If I set in this function the pragma macro, a call to multiply(...) will run on all threads. Now assume that somewehere else I want to do many vector multiplication : void many_multiplication

问题 I have an issue with OpenMP. MSVS compilator throws me "pragma omp atomic has improper form" . I don't have any idea why. Code: (program appoints PI number using integrals method) #include <stdio.h> #include <time.h> #include <omp.h> long long num_steps = 1000000000; double step; int main(int argc, char* argv[]) { clock_t start, stop; double x, pi, sum=0.0; int i; step = 1./(double)num_steps; start = clock(); #pragma omp parallel for for (i=0; i<num_steps; i++) { x = (i + .5)*step; #pragma

问题 I'm creating a basic prime number checker, based on C - determine if a number is prime , but utilising OpenMP. int isPrime(int value) { omp_set_num_threads(4); #pragma omp parallel for for( int j = 2; j * j <= value; j++) { if ( value % j == 0) return 0; } return value; } When compiling with -fopenmp , GCC version 4.7.2 is erroring, stating invalid controlling predicate with respect to the for loop. It looks like this error is caused by the j squared in the for loop. Is there a way I can work

问题 I have a loop in my C++/OpenMP code that looks like this: #pragma omp parallel for for(unsigned int i=0; i<count; i++) { // do stuff } When I compile it (with Visual Studio 2005) I get the following error: error C3016: 'i' : index variable in OpenMP 'for' statement must have signed integral type I understand that the error occurs because i is unsigned instead of signed, and changing i to be signed removed this error. What I want to know is why is this an error? Why aren't unsigned index

问题 I'm creating a Photoshop Plug In on OS X (Basically a Bundle / DyLib). I'm using Intel Compiler and uses OpenMP by linking against OpenMP ( libiomp5 ). When I use Static Linking it crashes Photoshop (Only on OS X, on Windows it works). So I tried dynamic linking. The host, Photoshop, uses by itself libiomp5.dylib which is available on its Framework folder. So, on Xcode I set on the Linking Part the Runpath Search Paths to @executable_path/../Frameworks/ yet when I try to load it on Photoshop

问题 I'm creating a Photoshop Plug In on OS X (Basically a Bundle / DyLib). I'm using Intel Compiler and uses OpenMP by linking against OpenMP ( libiomp5 ). When I use Static Linking it crashes Photoshop (Only on OS X, on Windows it works). So I tried dynamic linking. The host, Photoshop, uses by itself libiomp5.dylib which is available on its Framework folder. So, on Xcode I set on the Linking Part the Runpath Search Paths to @executable_path/../Frameworks/ yet when I try to load it on Photoshop

问题 I'm trying to make a for loop multi-threaded in C++ so that the calculation gets divided to the multiple threads. Yet it contains data that needs to be joined together in the order as they are. So the idea is to first join the small bits on many cores (25.000+ loops) and then join the combined data once more at the end. std::vector<int> ids; // mappings std::map<int, myData> combineData; // data per id myData outputData; // combined data based on the mappings myData threadData; // data per

问题 I am trying to parallelize a large program that is written by a third-party. I cannot disclose the code, but I will try and give the closest example of what I wish to do. Based on the code below. As you can see, since the clause "parallel" is INSIDE the while loop, the creation/destruction of the threads are(is) done with each iteration, which is costly. Given that I cannot move the Initializors...etc to be outside the "while" loop. --Base code void funcPiece0() { // many lines and branches

问题 I am working on an Fortan code that already uses MPI. Now, I am facing a situation, where a set of data grows very large but is same for every process, so I would prefer to store it in memory only once per node and all processes on one node access the same data. Storing it once for every process would go beyond the available RAM. Is it somehow possible to achieve something like that with openMP? Data sharing per node is the only thing I would like to have, no other per node paralellisation

问题 I have a proprietary library (>150,000 lines) of quantum mechanics C++ code that relies on OpenMP for parallisation. This code used to compile fine with Xcode 4.6 and its' real GCC compiler, but the LLVM compiler that ships with Xcode 5 doesn't seem to support OpenMP. My code is developed on a Mac but needs to be portable to non-Apple hardware such as massively parallel supercomputers, so re-writing the code is not an option. Does anyone know of a suitable compiler that can be used? Many